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Abstract
Background Insulin works to control blood sugar levels by sending signals to liver, muscle and fat cells to bring in sugar out of the blood. Obesity, hyperinsulinemia, hyperglycemia, and hyperlipidemia are only a few of the interconnected metabolic disorders that are frequently linked to these diseases. A statistical procedure called the Homeometric Assessment Model (HOMA) is used to determine the insulin resistance and pancreatic cell activity. (HOMA - IR). Both are determined using insulin and fasting plasma glucose (FPG), but utilizing different formulas. Although investigations based on a modified version of HOMA using connective peptide concentrate (C-peptide) are shown, they are extremely scarce.
 Objective: A study of the effect and help (TyG & HOMA-IR) of knowing insulin resistance and early detection of prediabetes.
 Subjects, Material, and Method: Analytical cross-sectional and cohort designs are the two types of statistical designs. The study was conducted on 160 volunteers, recruited at the beginning of the study and chosen from an age group based on the study data and the preliminary analysis, with ages ranging from (40-70 years). They were separated into two groups: the first group includes 80 individuals, after adopting an average body mass index of more than 25, who suffer from insulin resistance, and the second group includes 80 healthy individuals who do not suffer from insulin resistance and whose body mass index is less than 25. It was determined Blood glucose, lipid profile, and HBA1C using Cobas c111 on serum samples from both groups. Fasting insulin was determined using Cobas E411 and serum glycine using ELISA kits.
 Results: After conducting the statistical procedures for the results of the subjects for each of TyG, HOMA - IR, it was found that there was a significant change and p- value (0,00).
 Conclusion: HOMA-IR has had an important role in the evaluation, detection and prognosis of prediabetes. It also helps detect early complications associated with T2DM and helps determine the best treatment options. It also found that the TyG index beats the HOMA-IR for predicting prediabetes. It has the best potential for early detection and prevention of prediabetes
 
 
 
 
 
 
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